I like Cities: Skylines, but struggle at building roundabouts. Turns out, despite being safer than intersections, they're also tricky to design in real life - small tweaks can ruin traffic flow.
They're designed iteratively. This is a pain for developing countries without resources to test options. But AI could help auto-generate diverse and valid design options.
In a new paper, researchers propose using Generative Flow Networks (GFlowNets) to sample varied roundabout layouts. Their approach works by constructing layouts step-by-step, maximizing rewards for realism, diversity, and safety.
They also use a clever approximation during training. Rather than simulating traffic, they quickly check road intersections to focus the search (This sped up training by 200x).
The authors tested their generated roundabout designs on simulated road scenarios of different complexity. Their model generated more diverse designs than rule-based or reinforcement learning approaches while maintaining realism and traffic flow.
Plus, as road connections increased, the model kept discovering novel options without compromising quality.
I thought this paper was an awesome proof-of-concept for auto-generating better roundabouts with AI, and I especially liked the authors' angle of leveraging this technology to specifically help developing countries. This could help them design higher-quality transportation networks faster and cheaper.
TLDR: Roundabouts are costly to design. New paper demonstrates how AI can generate diverse, valid roundabout designs quickly to cut costs and raise quality. Helpful for infrastructure in developing countries.
Full summary here. Paper is here.
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